.png){kind=icon}
Return
Structural Information-Based Image Quality Assessment Using LU Factorization
.png){kind=icon}
PRE
AI
DOI：10.1109/TCE.2009.4814430.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The goal of the objective image quality assessment is, to quantitatively measure the image quality of an arbitrary image. The objective image quality measure is desirable if it is close to the subjective image quality assessment such as the mean opinion score. linage quality assessment algorithms are generally classified into two methodologies: perceptual and structural information-based. This paper proposes a structural information-based image quality assessment algorithm, in which LU factorization is used for representation of the structural information of an image. The proposed algorithm performs LU factorization of each of reference and distorted images, from which the distortion map is computed for measuring the quality of the distorted image. Finally, the proposed image quality metric is computed from the two-dimensional distortion map. Experimental results with the laboratory for image and video engineering database images show the efficiency of the proposed method, calibrated by linear and logistic regressions, in terms of the Pearson correlation coefficient and root mean square error. In commercial systems, the proposed algorithm can be used for quality assessment Of mobile contents and video coding, which effectively replaces the peak signal to noise ratio or the mean square error.
Keywords:
Image quality assessment
structural information
LU factorization
DMOS
logistic regression
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
10.9
Papers:
5.3K
Citations:
6.8K
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveShareSave no more
no more